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Kernel regression estimates of growth curves using nonstationary correlated errors

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  • Ferreira, Eva
  • Núñez-Antón, Vicente
  • Rodríguez-Póo, Juan

Abstract

We study the nonparametric estimation of the average growth curve under a very general parametric form of the covariance structure that allows for monotone transformation of the time scale. We also investigate the properties of optimal bandwidth selection methods and compare the results with those obtained under stationarity.

Suggested Citation

  • Ferreira, Eva & Núñez-Antón, Vicente & Rodríguez-Póo, Juan, 1997. "Kernel regression estimates of growth curves using nonstationary correlated errors," Statistics & Probability Letters, Elsevier, vol. 34(4), pages 413-423, June.
    • Handle: RePEc:eee:stapro:v:34:y:1997:i:4:p:413-423
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    References listed on IDEAS

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    1. Hart, Jeffrey D. & Wehrly, Thomas E., 1993. "Consistency of cross-validation when the data are curves," Stochastic Processes and their Applications, Elsevier, vol. 45(2), pages 351-361, April.
    2. Altman, Naomi Simone, 1993. "Estimating error correlation in nonparametric regression," Statistics & Probability Letters, Elsevier, vol. 18(3), pages 213-218, October.
    3. Wolfgang Härdle & Philippe Vieu, 1992. "Kernel Regression Smoothing Of Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 13(3), pages 209-232, May.
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    Cited by:

    1. Vicente Núñez-Antón & Juan Rodríguez-Póo & Philippe Vieu, 1999. "Longitudinal data with nonstationary errors: a nonparametric three-stage approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 8(1), pages 201-231, June.
    2. Benhenni, K. & Rachdi, M., 2006. "Nonparametric estimation of the regression function from quantized observations," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 3067-3085, July.
    3. Ferreira García, María Eva & Núñez Antón, Vicente Alfredo & Rodríguez Poo, Juan M., 1999. "Two-Stage Nonparametric Regression for Longitudinal Data," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    4. D. Benelmadani & K. Benhenni & S. Louhichi, 2020. "The reproducing kernel Hilbert space approach in nonparametric regression problems with correlated observations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(6), pages 1479-1500, December.
    5. Yuanhua Feng & Thomas Gries, 2017. "Data-driven local polynomial for the trend and its derivatives in economic time series," Working Papers CIE 102, Paderborn University, CIE Center for International Economics.
    6. Karim Benhenni & Mustapha Rachdi & Yingcai Su, 2013. "The effect of the regularity of the error process on the performance of kernel regression estimators," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(6), pages 765-781, August.

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